Is it time to retire the ‘AI’ brand to bolster adoption among video creators?

AI tools have put the video creator economy in sharp focus over recent months. AI video generators like Runway and OpenAI’s Sora have provided a tangible example of not just AI’s capability in video, but its transformative impact more generally. AI has been boosting productivity by automating processes across different industries for many years. But given that most of us are TV, movie, or social video consumers, these AI generated videos have cut through to capture the public imagination. They have provided an easy to digest example of how revolutionary AI can be. 

However, as awareness grows, so do the preconceptions about the technology. AI has become a loaded term that is used to communicate specific messages. Many businesses are keen to promote their AI investments (no matter how small) because it is a by-word for innovation, productivity, and efficiency. They believe this is the message investors want to hear because they understand the upsides to financial performance. However, AI is also a polarising term that carries negative connotations. Chief among them is the displacement of human beings, whether that is physically in the workplace by reducing jobs, or creatively by making it easier for beginners to achieve high-quality results.  

Video creator AI perspectives

These split opinions also exist among video creators. Nearly half (45%) of video creators associate AI with productivity benefits (MIDiA’s video creator survey, Q2 2024). They believe that the more workflows are streamlined using AI tools, the more videos they can produce. Similarly, around a third (31%) are excited by how AI will change video making. They believe it will help transform their output for the better. However, more than a quarter (28%) do not like the use of AI in video, an opinion that is equally strong across all experience levels:  24% for beginners, 30% for intermediates, and 25% for advanced creators. However, what is most concerning for AI tools developers is the significant portion of video creators who want to use AI tools but do not know how to apply them: 41%, 30%, and 22% of beginners, intermediates, and advanced creators, respectively. 

Bridging the disconnect

So how can developers of AI tools bridge this disconnect? Part of this issue is caused by AI tools being in the early adopter stage. While a portion of video creators are willing to try AI tools that could improve their workflows, a portion will just stick with what they know. Meanwhile, adoption is also being impacted by AI innovation coming from new entrants in the video creator space. Not only will it take time for creators discover companies like Runway, but it will also take time to trust them. 

Then there is the workflow integration issue. Many AI tools are launching their products with the expectation that creators will figure out where to fit them in, rather than explaining how best to implement them. These providers need to explain the context behind their tools, what the best results look like, and why they are beneficial in the long run. This could mean demonstrating how such tools fit into a traditional video creator workflow, or how they fit into a new work stream of AI-only products (examples of which can be found in my previous blog post). 

A marketing re-think

However, there is also the question of how these tools are marketed. When it comes to monetisation, video creators are more willing to spend on tools based on the features they offer at 58%. This is well above other incentives such as discounts (18%) or subscriptions (5%). Therefore, a marketing strategy that puts features first has stronger monetisation potential. As many video creators are sceptical about AI, a swathe of new features branded as AI-powered could cause them to disengage – despite AI being a byword for innovation. To counter this, tools providers should focus less on the AI aspect and more on the creative / workflow benefit. Ultimately, creators want to make purchasing decisions based on what tools can empower their creativity or soothe their pain points. By focusing on the workflow benefits, tools providers will not need to worry about educating those creators ‘interested in AI tools but do not know where to start’. They just need to communicate how a specific tool can help them. 

However, this approach must come with a caveat. Any AI tool that poses ethical questions – especially around copyright – should label AI’s involvement. Labels may also be needed for published videos for those with AI concerns. This approach will prevent a backlash from creators and audiences who may feel duped otherwise. The fine line here is the difference between labelling and marketing. By marketing a product as AI-powered, the tools provider is discounting adoption among some creators before selling the benefit of the product. It may well be that an AI sceptic could be convinced otherwise, if they knew about the benefits first. Companies will need to carefully navigate their communications strategy to talk up features to creators, remain transparent about AI-powered output (or its implications on rights, etc.) while keeping the ‘AI’ word for communications to investors and industry partners, where desirable.